Group Title: Working paper Farming Systems Research Group, Michigan State University no. 1
Title: Farming systems research and agricultural economics
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Permanent Link: http://ufdc.ufl.edu/UF00095071/00001
 Material Information
Title: Farming systems research and agricultural economics
Series Title: Working paper Farming Systems Research Group, Michigan State University no. 1
Physical Description: 20 p. : ; 28 cm.
Language: English
Creator: Crawford, Eric W. ( Eric Winthrop )
Michigan State University -- Farming Systems Research Group
Donor: unknown ( endowment ) ( endowment )
Publisher: Michigan State University, Farming Systems Research Group
Place of Publication: East Lansing
Publication Date: 1981
Copyright Date: 1981
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Genre: non-fiction   ( marcgt )
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Statement of Responsibility: by Eric W. Crawford.
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Bibliographic ID: UF00095071
Volume ID: VID00001
Source Institution: University of Florida
Holding Location: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
Resource Identifier: oclc - 317069927

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Farming Systems

Research Group

MICHIGAN STATE UNIVERSITY


The Farming Systems Research Group at Michigan State University is drawn from
the departments of Agricultural Economics, Agricultural Engineering, Animal
Science, Crop and Soil Science, Food Science and Human Nutrition, Sociology,
Veterinary Medicine, and supported by the International Agriculture Institute of
M.S.U. and the U.S. Agency for International Development through a matching
strengthening grant under the Title XII program.







Farming Systems Research Group
Michigan State University




The Farming Systems Research Group at Michigan State University, supported
by Title XII Strengthening Grant Funds from the U.S. Agency for International
Development, and administered by the Institute of International Agriculture,
has included Dr. Jay Artis, Department of Sociology; Dr. Robert J. Deans,
Department of Animal Science; Dr. Merle Esmay (and Dr. Robert Wilkinson),
Department of Agricultural Engineering; Dr. Eric Crawford, Department of
Agricultural Economics; Dr. Russell Freed, Department of Crop and Soil
Sciences (also representing Horticulture); Dr. Al Pearson, Department of
Food Science and Human Nutrition; Dr. Tjaart Schillhorn Van Veen, Department
of Veterinary Medicine; with Dr. George Axinn, International Studies and
Programs and Agricultural Economics, Chair, and Ms. Beverly Fleisher,
graduate research assistant.


FARMING SYSTEMS
ECONOMICS


RESEARCH AND AGRICULTURAL


by Eric W. Crawford


Working Paper No. 1


June, 1981






THE MICHIGAN STATE UNIVERSITY FARMING SYSTEMS RESEARCH GROUP

WORKING PAPER SERIES


Paper No.

1.


2.

3.

4.


5.


6.

7.


8.



9.


10.


11.


12.


13.


Title

Farming Systems Research and Agricul-
tural Economics

Farming Systems Position Paper

Livestock Systems and Animal Health

Issues in Farming Systems Research --
an Agronomist's Perspective

Farming Systems Research As It Relates
To The Animal Sciences

Farming Systems Research Position Paper

The Farming Systems Research Approach in
the Agricultural Engineering Field

Issues in Farming Systems Research --
a Multidisciplinary Behavioral Science
Perspective

Farming Systems Research and
Agricultural Engineering

An M.S.U. Approach to Farming Systems
Research

The M.S.U. Farming Systems Research
Group Perspective

A Working Bibliography on Farming
Systems Research August, 1981

Social Impact, Economic Change, and
Development -- with illustrations
from Nepal


Author

Eric Crawford


Al Pearson

Tjaart Schillhorn van Veen

Russell Freed



Robert J. Deans

Jay Artis

Merle L. Esmay


George H. Axinn



Robert H. Wilkinson


Beverly Fleisher and
George H. Axinn






George H. Axinn and
Nancy W. Axinn







WORKING PAPER #1


Farming Systems Research and Agricultural Economics

by Eric W. Crawford*


Background

In its initial form, this paper was intended to generate discussion

within the Michigan State University Farming Systems Research Working Group.

At the outset, we agreed that it would be desirable to establish a common

understanding of what farming systems research (FSR) was all about. We also

hoped to learn something about the perspective, concepts, and methodology of

the different disciplines represented within our group. As we attempted to

define basic terms such as "farming system," not to mention "farming systems

research," it quickly became apparent that reaching this common understanding

across disciplines would not only be more time-consuming but also more impor-

tant than originally expected.

In the discussion papers, we therefore attempted to set forth our prelim-

inary understanding of FSR, how it related to other types of research and

problem-solving activities in our respective disciplines, and how the involve-

ment of other disciplines would contribute to our own work in FSR. The papers

were not an effort to advance the frontier of any particular discipline, but

rather to communicate enough of the perspective of each discipline so that

henceforth we could operate on the same wavelength. The papers--at least this

one--also reflect a personal viewpoint and a necessarily selective picture of

the disciplines represented.



*Assistant Professor of Agricultural Economics, Michigan State University.
Many thanks to other members of the FSR Working Group, and to Warren Vincent,
for helpful comments on earlier drafts of this paper.


June, 1981





-2-


What is Farming Systems Research?

In defining farming systems research (FSR), I feel it is desirable to

distinguish between the following two categories:

1. Research on the farming system (RFS), principally characterized by a

holistic or systems view, i.e., a focus on some or all major elements and

interactions of the farm operation, rather than on individual components such

as particular crop or animal production activities. RFS is therefore a broad

category of research. It encompasses but is not limited to disciplinary

research, i.e., research aimed at improving the theory or analytical methods

of a given discipline, provided the work is systems rather than component

oriented. Examples include simulation or econometric studies of the farm

household. In my view, RFS does not necessarily involve either a multidisci-

plinary team approach or contact with the farmer.

2. Farming systems research (FSR), described by Hildebrand (1977),

CGIAR/TAC 1978), and Gilbert, Norman, and Winch (1980), and carried out

largely in the international arena. To me, FSR is a subset of RFS. Its dis-

tinctive features are: (a) implementation by a multidisciplinary team of

scientists; (b) close contact between researchers and farmers; (c) recognition

of farmer goals and the relationship between the human and technical aspects

of the farming system; (d) an orientation toward generation of locally suited

technology for improving the productivity of the farming system; and (e) an

emphasis on field level rather than experiment station research activity.

The term "farming systems research" has been applied to programs which

vary significantly along several dimensions: (1) degree of farmer involve-

ment; (2) scope in terms of how many farming systems components and linkages

are considered; (3) size of the "recommendation domain" of the research, i.e.,

the breadth of the region or farm type for which the research is relevant; (4)





-3-


extent of experiment station versus farm level activity; and (5) degree of

multidisciplinary involvement.1 Programs labelled as FSR include those which

focus only on the cropping system or even more narrowly on particular key

crops such as maize, rice, or wheat, and those which are carried out largely

by biological scientists on the experiment station. Disciplinary studies

which are not oriented to technology generation are not commonly labeled as

FSR, yet I think they can be important sources of knowledge about the farming

system. This is why I define the broad category of RFS.

At the urging of international donors, FSR has been recently promoted and

undertaken largely by researchers concerned with small farm agriculture in the

Third World, whether at national or international research centers. However,

the FSR methodology is potentially suited to small and large farms alike, and

to North American and European farms as well as those in the Third World.

Nonetheless, the capacity of FSR to examine complex multi-enterprise farming

systems and to "give a voice" to the farmer is probably more beneficial in

Third World agriculture than in North America and Europe, where farms tend to

be more specialized and where farmers have the resources and education needed

for them to represent their own interests to the research and extension estab-



1For the sake of comparison, the definition of FSR given by Gilbert, Nor-
man, and Winch (1980) may be quoted in part:

Farming systems research views the farm or production unit and the
rural household or consumption unit--which in the case of small farmers
are often synonymous--in a comprehensive manner. FSR also recognizes the
interdependencies and interrelationships between the natural and human
environments. The research process devotes explicit attention to the
goals of the whole farm/rural household and the constraints on the
achievement of these goals. (GNW, 1980:2-3)

They prefer the term FSR for research which includes the active participation
of the farmer. They also state: "Research on a sub-system can be considered
part of the FSR process if the connections with other sub-systems are recog-
nized and accounted for." (GNW, 1980: 3)




-4-


lishment. For small or part-time farmers in developed countries, FSR may have

the same benefits it does in Third World countries.


What Does FSR Have to Offer?

From the standpoint of agricultural economics, FSR potentially contri-

butes to problem-solving by improving understanding of the farming system, and

by enabling more effective development of technology for raising farm produc-

tivity. Improved understanding results from: (1) description and analysis of

interdependencies among components of the farming system, and between the farm

household and its environment; (2) the conceptual perspective on goals, con-

straints, and processes brought from other disciplines represented on the FSR

team; and (3) insights gained from including the farmer's viewpoint.

Improved understanding has a disciplinary payoff in terms of more power-

ful theory and analytical methods for research on the farm household.2

Improved understanding also leads to better diagnosis of problems and con-

straints within the farming system, and hence to the development of more pro-

ductive agricultural technology via new varieties, input combinations, cul-

tivation practices, etc. Thus, there is a close tie between problem identifi-

cation and prescription of solutions.

A domestic U.S. application of the systems approach to problem-solving is

research on integrated pest management. Chemical pest control is replaced by

a combination of biological and chemical controls, changes in crop mix and

cultivation, and more careful monitoring of pest populations. This approach

relies on information from several disciplines, including entomology, soil and

plant science, agricultural economics, and agricultural engineering, as well

as from the farmer. In West Africa, research on animal traction also


2By "more powerful" I mean having greater scope and/or predictive accuracy.





-5-


represents a systems approach to problem-solving. Low productivity and dec-

lining soil fertility under hand hoe bush fallow farming is addressed by a

mixed animal/crop farming system in which animal power breaks labor

bottlenecks, allows the incorporation of manure and crop residues to improve

soil fertility and thus crop yields, and provides a source of non-farm revenue

from animal-drawn carting.

The international brand of FSR was developed largely to address the prob-

lem of lack of adoption of improved agricultural technology. Low adoption

rates were a sign that important factors had been excluded in the technology

design process. FSR was intended to account for these missing factors, such

as: (1) interactions involving crop and animal enterprises and farm and non-

farm activities; (2) the performance of the technology under actual on-farm

conditions; and (3) economic and socio-cultural factors affecting acceptabil-

ity. Whether FSR-so defined--will in fact successfully overcome the "adop-

tion problem" remains to be seen.


Principles and Concepts of Agricultural Economics
re: FSR-Background for the Non-Economist

In studying a farming system, what analytical structure would be employed

by an agricultural economist? What variables and relationships would be exam-

ined? The following is a cursory and personally selective discussion of these

questions.

Farm households are considered to engage in several categories of

economic activity: production, consumption, marketing (buying and selling of

goods and services), and saving and investment. A common reductionistt"

approach is to study each of these activity categories in isolation from the

others. However, recent theorizing (both for U.S. and Third World farm types)

has emphasized the joint nature of these activities and the decisions




-6-


involved.3 For example, what the farm household produces is determined in part

by what it needs for consumption. Such interdependencies are particularly

salient for semi-subsistence farm households. This implies the need for a

more holistic approach, which has led to development of the "theory of the

farm household."

A thumbnail sketch of the theory of the farm household includes the fol-

lowing elements:

1. Households are assumed to maximize utility subject to various con-

straints. Utility is derived from household-produced farm and non-

farm goods, goods purchased from the market, and leisure. Goods and

leisure generate utility when they are consumed.

2. The constraints on utility maximization include:

(a) household production functions for farm and non-farm goods;

(b) a time availability constraint (time is used as an input to

household production, as well as for leisure);

(c) a budget constraint, which states that total expenditures must

be no greater than total income (including wage earnings and

income from assets).

As one moves from pure theory to applied research and farm management

studies, the variables and functional relationships associated with the farm

household must be specified in more concrete detail. Information of the fol-

lowing type is commonly sought:

1. Resource inventories. Economics is concerned fundamentally with the

allocation of resources to achieve specified goals. Thus, a start-

ing point is the identification of the stocks of resources held by


3The next section of the paper contains a more detailed discussion of these
points.




-7-


the household, including land, buildings and machinery, working cap-

ital, family labor, and crop and livestock holdings.

2. Resource utilization. What are the flows of resources through the

farm system? Such flows include labor use, cash flow, machinery

use, etc. A high proportion of the data collected by large-scale

farm management surveys in the Third World results from documenting

these resource flows. Since household activities compete for a com-

mon set of resources, it is important to determine the flows of

goods and services among components within the farm household sys-

tem.

3. Description of household activities.

a. Farm production:

crop and livestock enterprises (rice, dairying, etc.)

-- production operations (weeding, harvesting, etc.)

b. Non-agricultural activities, including domestic household

tasks, crafts, trading, and other self-employed occupations

undertaken by household members.

c. Other off-farm activities, primarily wage employment.

4. Functional relationships and technical parameters.

a. Technical input-output coefficients for the production

processes.

b. The parameters of household consumption demand.

c. Marketing relationships, e.g., the timing and characteristics

of items purchased and sold.

d. Saving and investment behavior.

5. Costs and returns. These are a function of prices, which are a key

economic variable.




-8-


a. Operating costs associated with production and marketing.

b. Fixed costs, e.g., depreciation, interest, taxes, insurance,

etc. These are the costs of owning capital assets.

c. Sale prices for farm output; purchase prices for farm inputs

and family consumption items.

d. Wage rates for labor

6. Goals, attitudes and operating procedures.

a. Household goals, i.e., what does the household wish to achieve

through the use of its resources? Are its goals primarily pro-

fit or growth oriented, or more concerned with security and

maintenance of family well-being?

b. Preferences, including preferences for one type of farm

activity (e.g., cropping) over another (e.g., livestock rais-

ing). Attitudes toward risk are also important.

c. Operating procedures. Does the farmer have standard methods or

strategies which he follows in making decisions, e.g., stra-

tegies for reducing the impact of uncertainty in the production

process?

7. Institutional and environmental variables.

a. How do the markets for resources function: for farm inputs and

outputs, for land and labor, and for credit? Does the farmer

have access to these markets? How reliable are they?

b. What is the physical environment of the farming system: soils,

rainfall, altitude, etc.?

c. Related to (a), are there important rules affecting access to

resources, such as rules governing land allocation and land

tenure?




-9-


Household goals and preferences, and institutional and socio-cultural

variables, are a special focus of social scientists, including agricultural

economists. Consequently, one of the appropriate contributions of the agri-

cultural economist as an FSR team member is to view the farming system within

the larger institutional and policy framework, and to evaluate the impact of

market and price factors on the farm household's welfare.


Implementing FSR: Some Disciplinary Challenges

In previous discussions of the problems of organizing and implementing an

FSR program, the focus has been on the difficulties of a multidisciplinary

team approach, and on procedures for on-farm research (Norman, 1980; Rohrbach,

1980; CGIAR/TAC, 1978). Relatively little attention has been paid to ways in

which the analytical state of the art in the various disciplines poses obsta-

cles to successful research on farming systems.

In this section of the paper, I will try to sketch a few of the principal

theoretical, methodological, and empirical data limitations on the economic

analysis of the farm household system. My emphasis here is on the broad study

of existing farming systems and their response to proposed new technology or

policies, rather than on FSR for experimental development and field testing of

new technology.

As in any systems approach, FSR does not require exhaustive enumeration

of system activities, but entails instead a focus on the essential ones. The

premise of FSR is that the study of farm households will be strengthened if

the scope of analysis is broadened to incorporate formerly neglected activi-

ties and interactions which are now recognized as crucial for understanding

household behavior.

This implies an increase in analytical complexity along several lines.

First, recognition that rural households are diverse rather than homogeneous,




- 10 -


and that variability in agroclimatic environment leads to location-specific

constraints and opportunities, calls for analysis of many rather than a few

household types. Second, the holistic perspective of FSR calls for an

increase in the number of household activities considered in the analysis.

Livestock activities are important and should be viewed in conjunction with

cropping activities (McDowell and Hildebrand, 1980). It may often be desir-

able to examine self-employed non-agricultural enterprises in addition to on-

farm production and off-farm wage employment. Related to this is a require-

ment for expansion of the set of variables which enter the analysis. This

stems both from the larger number of activities being studied, as well as from

the recognition that agroclimatic and socio-cultural factors have economic

relevance.

Third, the analysis of farm household decisions must reflect reality more

closely. Aspects of importance are: (1) multiple goals and sequential

decision-making; (2) intrahousehold patterns of resource allocation; (3) the

interdependence between production decisions and those concerning credit,

marketing, consumption, savings, and investment; and (4) a dynamic, long-term

decision framework incorporating uncertainty.

Fourth, there is a need to recognize the interaction of the household

with its surrounding social and institutional environment. The analysis

should consider macro factors (market processes, institutions, and policies)

which impinge on the farm.

Farming systems studies are therefore threatened with the "curse of

dimensionality"-so many factors to analyze that a solution to the research

problem may be infeasible (Anderson and Hardaker, 1979). Agricultural econom-

ists must not only learn to effectively integrate expertise from specialized

fields within their own discipline (e.g., production, consumption, investment,




- 11 -


marketing, decision-making under uncertainty), but also from biological and

physical sciences, and other social sciences. This is an intellectually

demanding process, even for systems scientists who are at home with a holistic

rather than reductionist focus (Dillon, 1976).

Can this be accomplished within current theory and methodology in agri-

cultural economics? This question is clearly beyond the scope of a short

paper, but let us briefly examine the current disciplinary capacity to: (a)

incorporate household activities and interactions more comprehensively; and

(b) incorporate more realistic decision-making processes.

Expanding the scope of analysis is constrained partly by the available

theory. Neoclassical microeconomics has traditionally examined the

household's producer and consumer behavior separately. Beginning at least

with Mellor (1965), efforts have been made to integrate production and con-

sumption decisions in a household framework.4 Nakajima (1969) developed essen-

tially neoclassical models for subsistence and commercial family farms which

incorporated consumption and labor market participation, but not non-

agricultural production or (explicitly) leisure. Becker (1965) introduced the

concept of the household as a producing not just a consuming unit, with domes-

tic commodities produced with factors including time. Many recent economic

models of the agricultural household, e.g., Barnum and Squire (1979), draw on

Becker's work. The interdependence of production and consumption decisions

within the Barnum and Squire model is accomplished technically by specifying

consumption elasticities which contain terms for the effect of exogenous vari-

ables on farm profits, and hence on household income and consumption.



4Chayanov's much earlier model (1966, written in the early 1900's) of the
peasant household was holistic, but his definition of the peasant household as
relying entirely on family labor has restricted relevance today.




- 12 -


The advantages of such models are: (1) they examine the household in an

integrated framework which is consistent with the accepted theory of producer

and consumer maximizing behavior; (2) their format and assumptions are by now

fairly standard, hence easily interpreted by other researchers; (3) when

expressed in mathematical form their properties (e.g., elasticities) can be

derived rigorously.

Several offsetting disadvantages should be noted. First, identifying the

utility maximizing solution to such models and their corresponding elastici-

ties often requires the imposition of so many simplifying assumptions that

only very un-complex household types can be analyzed. For example, although

the model of Barnum and Squire includes only one variable input (labor), and

two outputs (rice and domestic goods) which are consumed along with leisure

and a purchased good, they found it necessary to limit the complexity of the

problem even further ". . by omitting certain decision variables in order to

arrive at a solution that has policy content."5 (Barnum and Squire, 1979:

31).

A second, related disadvantage is the frequent need to restrict the func-

tional form of theoretical models in order to ensure the existence of

mathematical solutions. The result may conflict drastically with theoretical

axioms or observed reality. Third, although complexities such as multiple

goals, sequential decision-making, behavior over time, and stochastic varia-

bility have each been explored extensively in the literature (Day, 1977; Day

and Sparling, 1977), to this author's knowledge they have not yet been incor-

porated jointly in theoretical models of the farm household. Fourth, except


An extension of this model (Ahn, Singh, and Squire, 1979) incorporated pro-
duction of several crops using several inputs; farm commodities and profits
generated from a linear production system are fed into a linear expenditure
system to determine household consumption.




- 13 -


in linear models, the assumption of joint production or multiple inputs and

outputs tends to make solutions extremely tedious to obtain, or indeterminate

(Pollak and Wachter, 1975; Hart, 1978). Lastly, models of the household are

generally employed in the short run comparative statics context in which it is

possible to evaluate only small changes under ceteris paribus conditions.

Overall, theoretical models abstract from reality in a way which

emphasizes consistency, rigor, and computational convenience. This is more

appropriate in the context of disciplinary research than it may be in the con-

text of problem-solving research, which is the prime focus of FSR. Such

models are most useful in analyzing relatively simple farming systems (e.g.,

Asian rice monoculture)6 where restrictive assumptions and a short run per-

spective are justifiable.

Ability to expand the scope of farming systems studies is also limited by

available quantitative methods used to model the farm household. These

methods fall under three headings: econometrics, linear programming, and sys-

tems simulation.

Econometric models are attractive in part because comparatively well-

accepted procedures are available for estimating and evaluating their struc-

tural parameters. Econometric models can potentially incorporate features

such as behavior over time and stochastic variability. For example, random

coefficients production models have been discussed by Swamy (1974), Mount

(1974), and Harville (1977), although apparently they have not yet been

applied to an integrated farm household model.

Linear programing (LP) has been a powerful, widely used tool. It is

flexible enough to incorporate features such as multiple inputs and outputs,


Such farming systems are simple only in the sense that the production process
can be approximated in terms of one output and a few inputs.




- 14 -


behavior over time, and the effect of uncertainty. One drawback of LP models

is their inherent tendency to give unrealistically one-sided optimal solu-

tions, e.g., over-specialized cropping patterns. Also, very careful scrutiny

is needed to establish whether an LP model is sound, or whether apparently

plausible results were "forced" by artificial, a-theoretical manipulation of

constraints.7

Systems simulation models offer even greater flexibility of form. Com-

plex features can be readily accommodated and solutions still obtained (John-

son and Rausser, 1977; Crawford, 1980a). Model specification can be eclectic

and behavioral, facilitating use in problem-solving research (Johnson, 1977).

The principal drawback is that simulation models often cannot be proven

theoretically consistent. A related problem is the inadequacy of standard

statistical procedures for evaluating how well a simulation model performs;

considerable subjective judgment is also required.

Other difficulties arise in modelling the link between events at the

individual farm level and aggregate effects at the macro level. FSR focuses

primarily on the farm level, but the literature generally recognizes the

importance of national policies and the regional agricultural economy as fac-

tors influencing the appropriate direction of new technology development.

However, both theoretical and quantitative models are limited in their ability

to predict the macro effects of introduced new technology or policy interven-

tions. At the formal level, there are problems of bias in aggregating the

results of individual farm models to obtain a picture of regional impact (Day,

1963); in general, it is not legitimate to assume that the whole is equal to

the sum of the parts. In addition, evaluating the impact of new technology or


This drawback is shared to some extent by econometric and systems simulation
models.




- 15 -


policy interventions depends on the ability to analyze regional product and

factor markets. This moves the domain of the analysis from a partial to a

more general equilibrium framework, unless the situation can safely be simpli-

fied. Also, it is clear that the economic impact of a given development

intervention is heavily influenced by institutional and socio-cultural vari-

ables. However, rigorous prediction of socio-economic effects over time and

on a macro level is not yet feasible given available theory and analytical

methods in the social sciences.


Empirical Data Limitations

Achieving the holistic FSR approach will require better descriptive and

analytical understanding of several sub-systems of farm household activity

which hitherto have often been excluded. Perhaps the most important of these

is livestock activities, as noted above. Other areas deserving greater atten-

tion are: (1) self-employed non-agricultural occupations undertaken by farm

household members; (2) intrahousehold resource allocation and decision-making;

and (3) production and consumption/savings/investment behavior over time. All

four areas (including livestock) have been difficult to research for reasons

of required researcher mobility (in studying transhumant herders), access to

information (on self-employed and intrahousehold activities, often involving

women), and the cost and delay involved (time series data).

Current data collection methodologies are not entirely adequate, even for

partial analysis of farming systems. The recognized importance of considering

the diversity in farm household types and their agroclimatic environments--

rather than assuming homogeneity within broad categories (Crawford, 1980b;

Gerhart, 1975; Palmer-Jones, 1978) -- has encouraged reliance on detailed

large-scale farm management surveys. However, such surveys do not always

allow for the collection of the agronomic and socio-cultural information




- 16 -


needed for accurate identification of farm level constraints, or for the

analysis of complex features such as intercropped mixtures. Moreover, certain

kinds of information which may be crucial even for narrow economic analysis--

income, assets, food reserves--are known to be sensitive and hard to elicit

from respondents (Palmer-Jones, 1977).

As an alternative, the rapid survey technique used by some FSR practi-

tioners is less costly and easier to supervise. It brings knowledgeable

researchers into direct contact with farmers, using open-ended interviews in

place of minutely detailed questionnaires administered by enumerators. By

comparison to cost-route farm management surveys, from whose details the

essence of the farming system must be deduced, rapid surveys obtain less

detail but allow for the application of inductive reasoning and informed

intuition. Accordingly, they may ultimately give rise to a more profound

understanding of the farming system. A variant of this approach has been

developed by CIMMYT in East Africa (Collinson, 1979).


The Role of the Agricultural Economist in FSR

Although there is room for improvement in the systems research capacity

of the disciplinary tools of agricultural economics, agricultural economists

have a practical role to play in FSR programs at international and national

research centers, and as members of development project teams. As part of the

general goal of FSR, work by agricultural economists leads to improved under-

standing of existing farming systems. The particular contribution of agricul-

tural economists stems in part from the level at which they study the farming

system, namely the level of the whole farm or household rather than the level

of the plant/soil/water complex. Moreover, while assessing costs and returns

and resource constraints at the farm level is useful in solving some farmer

problems, economic analysis can and should define the farming system's




- 17 -


boundary more broadly, so that linkages with market institutions and the

effects of input/output price relationships are also examined. Because these

factors are critically important in determining the appropriate characteris-

tics of new technology, the FSR team has the opportunity to obtain an

indispensable contribution from the agricultural economist.

In turn, a wide range of disciplines can potentially assist in the solu-

tion of economic problems by elucidating critical variables, functional rela-

tionships, and constraints. For example, in studying investment behavior (or

the disposition of unspent income), it is desirable to know how social and

cultural factors determine the availability of investment opportunities and

who is allowed to take advantage of them. Or, in formulating a set of

improved cropping plans for farmer adoption, it is desirable to know which

crops are suited to local soils and rainfall, what their growing period is,

how yields respond to different cultivation practices, etc. More generally,

the economic feasibility of new technology or policy interventions is inextri-

cably tied to questions of technical, institutional, and socio-cultural feasi-

bility.

From a methodological standpoint, several disciplines are helpful in

facilitating economic research. As a mundane example, in mounting a farm sur-

vey, geographers can suggest which agroclimatic zones are relevant in strati-

fying the sample, statisticians can advise on sampling technique and data

analysis, biological scientists can advise on soil and water variables which

affect crop and livestock yields, and anthropologists can advise on important

cultural factors and techniques for informal interviewing.




- 18 -


REFERENCES



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